Abstract
The Sequential Multi-Block Partial Least Squares (SMB-PLS) model inversion is applied for defining analytically the multivariate raw material region providing assurance of quality with a certain confidence level for the critical to quality attributes (CQA). The SMB-PLS algorithm does identify the variation in process conditions uncorrelated with raw material properties and known disturbances, which is crucial to implement an effective process control system attenuating most raw material variations. This allows expanding the specification region and, hence, one may potentially be able to accept lower cost raw materials that will yield products with perfectly satisfactory quality properties. The methodology can be used with historical/happenstance data, typical in Industry 4.0. This is illustrated using simulated data from an industrial case study.
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